Effect of Droplet-Wake Phenomena on Mixing-Sensitive Pharmaceutical Reactions - Pharmaceutical Technology

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Effect of Droplet-Wake Phenomena on Mixing-Sensitive Pharmaceutical Reactions

Pharmaceutical Technology

On the basis of theoretical studies, the authors expected that if the flow regime was changed from vortex shedding to a steady-flow pattern (either closed wake or closed wake with recirculation), then the selectivity should decrease as a result of mixing effects. In the steady-wake regime, the fluid flows around the droplet. As the Reynolds number increases, a recirculation region directly behind the droplet develops and increases in size. Therefore, if a reaction occurs in the recirculation region, then the product P will continue to circulate in the wake and can only leave by diffusion. Fresh reactant will not be transported into the recirculation region except by diffusion. For this reaction system, this means that once the desired product is formed, it will remain in the recirculation region, and no fresh reactant will be transported into the region (except by diffusion). Therefore, as the iodine transfers phases, it will preferentially react with 3-iodo-l-tyrosine.

Figure 9
Results for the selectivity as a function of the molar-charge ratio in the steady-flow regime are shown in Figure 9. The continuous phase contained 30% glycerin. Fifteen experiments were run to generate this trend. As in the previous results, one sees that if the iodine is fed in excess, then the selectivity tends to drop quickly, thereby indicating that the second reaction is favored. If the l-tyrosine is fed in excess, the selectivity approaches 100%. At an initial molar-charge ratio of one, however, the selectivity for this set of experiments is approximately 74 2%. This value is substantially smaller when compared with the vortex-shedding regime (10% glycerin in the continuous phase) result of 85 2%.


In this study, a fast liquid–liquid reaction system showed experimentally how droplet wake dynamics can influence the selectivity of the reaction network. The main conclusions observed in this study are:
  • The wake dynamics of a droplets falling in a stagnant liquid change qualitatively with the viscosity, which translates into differences in the mechanisms of mixing and scalar transport.
  • For a parallel-consecutive reaction, network computational studies predict a low selectivity for a steady wake and increased selectivity for a vortex-shedding wake. The chaotic motion in a vortex-shedding wake causes stretching and folding of fluid elements, thus greatly enhancing liquid-phase mixing.
  • An experimental liquid–liquid reaction system—that is, iodination of l-tyrosine to form 3-iodo-l-tyrosine and 3,5-diiodo-l-tyrosine—was used to confirm computational predictions. The experimental study showed a substantial increase (~11%) in the selectivity when the reaction was run in the vortex-shedding regime.
  • In general, fast liquid–liquid chemical reactions, which occur almost exclusively in the bubble wake, show a strong sensitivity toward the wake-mixing characteristics.

To the best of the authors' knowledge, this is the first experimental study addressing the micromixing effects of bubbles and droplets. Understanding the effect of reactive mass transfer and local flow in such systems is crucial for maximizing reaction selectivity and minimizing the formation of byproducts. These byproducts can be detrimental to a process because additional manufacturing steps often are needed to separate, dispose, and rework the byproducts. Full-scale manufacturing can be severely constrained by parameters set early in process development. A poor understanding of multiphase reactive flows can impede efficient and effective scale-up. This article is intended to contribute to a better understanding and to the minimization of problems during scale-up of mixing sensitive reactions.


The authors acknowledge support of this work by Merck and Company. J.K. acknowledges funding by NSF through a CAREER Award (CTS-0093129) and NSF Grant CTS 02098764.

Jodi Raffensberger is a process engineer at Merck and Company. Benjamin Glasser is an associate professor, and Johannes G. Khinast* is an associate professor at the Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Rd., Piscataway, NJ 08854-8058. Khinast also is Marie Curie Chair at the TU Graz, Austria, tel. +43 316 873 7978,

*To whom all correspondence should be addressed.

Submitted: Dec. 12, 2005. Accepted: June 23, 2006. Keywords: Mixing sensitivity, multiphase flows, selectivity


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